Demonetization: a Visual Exploration and Pattern Identification of People Opinion on Tweets

BalaAnand, M.; Karthikeyan, N.; Karthick, S.; Sivaparthipan, C. B.

doi:10.1109/icsns.2018.8573616

Cited by 14 publications

(4 citation statements)

References 4 publications

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“…In addition with the resource allocation, the surveillance networks need the security level to the atmost degree for the efficient and reliable communication. Many video sensor applications are equipped with sensors such as agricultural assisting robot [30], industrial automation [31,36], and smart vehicles [32,35] where security is not prioritized as it is dealt with the sensor data [37,39]. But in the sensitive applications such as military surveillance areas, cyber agencies and banking sectors the ocular and streaming data is the primary source which need high protection.…”

Section: Our Contributionsmentioning

confidence: 99%

RETRACTED ARTICLE: Enhanced approach using trust based decision making for secured wireless streaming video sensor networks

Ramesh¹,

Yaashuwanth²

2019

Multimed Tools Appl

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The advances in the expanse of image sensors have made it conceivable to make highresolution picture sensors easily accessible. The amelioration of wireless interactive media sensor networks are found to be greatly increased due to the day to day usage of cameras, microphones and smart devices. A secured multi-hop routing mechanism is addressed in surveillance areas which could be incorporated to the multimedia sensors that are capable of peruse the detected data comprises of recorded images and videos. Also, malevolent sensor hubs could be interjected into the vigilance area in an untrusted environment. In this contemplated venture, a novel lightweight trust decision-making framework is accomplished for QoS clustering to give secure routing in both intercluster and intracluster communication. A quantifiable aberrant trust value is the variable determined by the Cluster Head (CH) for its Cluster Member (CM) inside the cluster. The LEACH (Low Energy Adaptive Clustering Hierarchy) protocol is adopted for group formation and also for the exchange of the trust values among the master nodes, member nodes and Base station. In this way, the correspondence overhead, likelihood of dynamic assaults for example sinkhole and black hole assaults mount by eavesdroppers can be reduced by maintenance of trust values by cluster heads rather than cluster members. Besides, in wireless streaming video sensor networks this approach authorizes us to predict and counteract malicious untrusted and flawed nodes. Simulation results using NS-2 is examined and the suggested trust decision-making model escalates the dependability, elasticity and low memory aloft in comparison with the current trust models adopted for wireless video sensor network security.

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Section: Our Contributionsmentioning

confidence: 99%

RETRACTED ARTICLE: Enhanced approach using trust based decision making for secured wireless streaming video sensor networks

Ramesh¹,

Yaashuwanth²

2019

Multimed Tools Appl

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“…The research and the experiments of VANETs are focused to utilize road safety information among vehicles to prevent accidents. The future vehicles will be equipped with sensors delivering various parameters (Balaanand et al 2015(Balaanand et al , 2018Maram et al 2019;Anupriya et al 2018), which will be displayed to the driver or transmitted to a RSU, which is a part of the VANET infrastructure. These parameters are also broadcasted to neighboring vehicles (Zeadally et al 2012).…”

Section: Vanets: An Overviewmentioning

confidence: 99%

Investigation of Secure Vekit Web Interface for Preventing Environment Pollution

Balaji¹,

Selvam

2020

Transport

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This paper describes a new system – Vehicle Kit (VEKIT), which uses a secure web-based interface for the authentication and monitoring of Vehicular Ad-Hoc Network (VANET) infrastructure and for preventing environment pollution. This paper presents the hazards caused by the usage of bags made of plastic material and proposes the design of VEKIT, which is to be installed in the vehicles for reducing the usage of such carry bags up to 75%. The survey results prove that the proposed VEKIT approach is very much relevant to solve the pollution problem faced by various countries. This novel application adds value to the future VANET projects by helping the countries to prevent pollution. The web interface of VEKIT presented in the paper can also be used to monitor the vehicles for their authenticity. A secure architecture is proposed for the usage of VANET in transport related projects.

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“…4b), and even the two Bdistinguishable EEG^signal can be detected by this arrangement. The fractional sampling rate of the AAWT gives shift-invariance, analytic covering, and flexible time-frequency covering [3,9,14,79,7]. This analytic base provides the In AAWT, obtaining the real transformation includes an iterated filter bank [17,72] that is designed with the combination of sums and differences of the one low pass channel for negative-frequency and two pass channels for positive frequency channels as shown in Fig.…”

Section: Decomposition Using Adjustable Analytic Wavelet Transform (Aawt)mentioning

confidence: 99%

A KSOM based neural network model for classifying the epilepsy using adjustable analytic wavelet transform

Ashokkumar

MohanBabu

Anupallavi

2019

Multimed Tools Appl

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Epilepsy is a nervous disorder occurring in the cerebral cortex location of the brain which is caused by irregular harmonization of neurons. Since the existence of this disorder is between the neurons, it is tedious to diagnose correctly. Research works of epilepsy mostly done on an Electroencephalogram (EEG) signals for analyzing the neuron activity of the brain during seizures. Analyzing the continuing EEG reports manually for a patient affected by epilepsy is time-consuming, and it needs a large storage volume. The proposed paper is based on a unique method for detecting epileptic seizures by Adjustable Analytic Wavelet Transform (AAWT). This work is also focused on testing the practicability of utilizing the Kohonen network maps for predicting the dynamics of the brain states in the form of the trajectory which may provide the occurrence of the seizure event. AAWT is applied on each EEG signal to decompose EEG signals into the sub-band signals. The fractal dimension is applied to these sub-bands signals as a discriminating feature due to its nonlinear chaotic trait. The received solutions are fed into Kohonen self-organizing network map (KSOM) to get a stable performance rate for the categorization of an epileptic seizure. The results proved that the introduced methodology achieved 98.72% sensitivity, 93.90% specificity, 93.03% selectivity, and 94.12% efficiency than the existing models and provided promising classification accuracy. Keywords Epilepsy . Electroencephalogram (EEG) . Adjustable analytic wavelet transform (AAWT) . Fractal dimension . Kohonen self-organizing network map (KSOM)

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Demonetization: a Visual Exploration and Pattern Identification of People Opinion on Tweets

Cited by 14 publications

References 4 publications

RETRACTED ARTICLE: Enhanced approach using trust based decision making for secured wireless streaming video sensor networks

RETRACTED ARTICLE: Enhanced approach using trust based decision making for secured wireless streaming video sensor networks

Investigation of Secure Vekit Web Interface for Preventing Environment Pollution

A KSOM based neural network model for classifying the epilepsy using adjustable analytic wavelet transform

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